Archaeologists Uncover 3 Never-Before-Seen Mayan Cities
The cities, arranged in a triangular pattern, rest roughly three miles apart from one another. They were incorporated during a period known as the 'middle preclassic' (1,000-400 B.C.), and remained inhabited until about 1,100 years ago. One site of particular interest to archaeologists, dubbed 'Los Abuelos' or 'the Grandparents,' contains stone sculptures of a man and woman which researchers believe depict the ancestors of the city's citizens. They posit that this site may have served as a ceremonial or religious center.The second newly discovered city, dubbed 'Petnal,' features a 108-foot tall flat-topped pyramid which contains a separate room containing murals. Though most of the artwork has degraded, scientists were able to identify red, white, and black colors; however, further analyses will be required to determine what the murals actually depicted. The third city, Cambrayal, features an intricate series of canals which begin at a water reservoir atop the city's palace. Archaeologists believe these waterways were used for removing waste."It's especially exciting to learn about the Los Abuelos site," Megan O'Neil, an associate professor of art history at Emory University who was not part of the excavation team, told Live Science. O'Neill added that the stonework found at the sites "are especially poignant and are similar to many other examples of Maya people making offerings to vital sculptures and connecting with their ancestors by interacting with sculptures from the past." She believes these recent discoveries will "help reconnect items in private and museum collections with their places of origin and deposition, helping return memory to those ceramics, to these sites, and to Maya people living in this region and across the world."Archaeologists Uncover 3 Never-Before-Seen Mayan Cities first appeared on Men's Journal on Jun 9, 2025
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Fox News
2 days ago
- Fox News
Researchers discover 2,500-year-old honey residue in ancient bronze jars
Researchers recently made a sticky discovery. They found 2,500-year-old honey, sealed in a vessel and buried underground for nearly three millennia. The residue was found in bronze jars at an underground shrine in Paestum, an ancient Greek settlement in modern-day Campania, Italy. The artifacts date back to the 6th century B.C. The jars were first found by archaeologists in 1954, but the residue in them has eluded experts – until now. In a study published by the American Chemical Society on July 30, experts concluded that the waxy residue was once honey. Luciana Carvalho, a research associate at the University of Oxford, told Fox News Digital the substance bears little resemblance to the golden honey in most modern-day cupboards. "Ancient honey was quite different from the clear, smooth honey we buy today," she noted. "There was no ultra‑filtration, no pasteurization and no synthetic pesticides in the landscape." The chemical results "strongly" suggested that the jars held raw honeycomb, rather than a blended product like most modern honey. "If honey had been mixed with milk, for example, we would expect to see extra fatty acids in the residue – and we don't," she said. But the raw honeycomb has dramatically changed over the millennia. Along with fellow researchers Elisabete Pires and James McCullagh, Carvalho found that the sugar gradually became dark and acidic. "After 2,500 years, almost all the original sugars have broken down [and been] eaten by microbes, so the residue isn't sweet anymore." "[The] sugars slowly reacted with proteins in a kind of slow-motion browning process, similar to what happens when bread bakes, turning it darker and more acidic," she said. Because of that, the remaining residue isn't exactly pleasant to eat, according to the expert. "What survives now is a waxy residue with a slight tang and virtually no sweetness," Carvalho noted. "After 2,500 years, almost all the original sugars have broken down [and been] eaten by microbes, so the residue isn't sweet anymore." As for the vessels, Carvalho said the bronze jars have cork discs that seal their necks, which points to "careful storage of something valuable." The copper-alloy jugs were found in a sealed, underground shrine, suggesting that they were left there as part of a ritual. "Inside, the residue clung to the bottoms and sides, exactly what you'd expect if raw honeycomb had been placed inside and slowly dried out over centuries," she said. "We hope our approach will be used to identify honey residues in other museum collections so we can learn more about ancient beekeeping and the role of honey in diet, medicine and ritual life." Researchers in the 1980s previously believed that the honey was a mixture of wax, fat and resin, with Carvalho noting that past research was limited by less precise tools. "Those methods were great for detecting fats and waxes but couldn't easily pick up sugars or proteins without extra chemical steps," she said. "In our study we used multiple modern techniques designed to detect different types of molecules, including sugars and proteins, even if these are present at trace levels, with instruments far more sensitive than anything available in the 1980s." She also noted that the discovery had strong collaboration from multiple groups, including museum curators, conservators and specialized scientists. "We hope our approach will now be used to identify honey residues in other museum collections so we can learn more about ancient beekeeping and the role of honey in diet, medicine and ritual life," Carvalho said. The latest research adds to a number of ancient food-related discoveries this year, which are extremely rare occurrences. In Guam, 3,500-year-old rice was recently found, making it the earliest known evidence of rice in Remote Oceania. Earlier in 2025, archaeologists uncovered a well-preserved loaf of ancient bread in Turkey, dating back to the Bronze Age.
Yahoo
07-08-2025
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An AI System Found a New Kind of Physics that Scientists Had Never Seen Before
"Hearst Magazines and Yahoo may earn commission or revenue on some items through these links." Here's what you'll learn when you read this story: For all the problems AI is causing society, one of its greatest benefits lies in the world of science. A new study focused on the chaotic dynamics of dusty plasmas found that, when trained properly, AI can actually discover new physics all on its own. By providing the most detailed description of this type of matter, the AI corrected long-held theoretical beliefs about how particles behave inside a dusty plasma. In more ways than one, artificial intelligence is making the world worse. Generative AI now spews countless amounts of 'AI slop,' and in classrooms, AI is slowly eroding critical thinking skills, which are… you know… critical. That's not even mentioning AI's unfortunate role as environmental decimator and job destroyer. Luckily, some artificial intelligence and machine learning (ML) models have grander ambitions than ripping off beloved animators and mass-producing essays at an eighth-grade reading level. Take, for instance, a new ML model developed by a team of Emory University scientists. Typically, machine-learning algorithms are used as a tool to help scientists sift through immense amounts of data or optimize experiments, but this particular ML model actually discovered new physics on its own—at least, as it relates to dusty plasma. You're likely familiar with plasma—that fourth state of matter that actually makes up 99.9% of all ordinary matter in the universe. Dusty plasma is simply the same mix of ionized gas, but with charged dust particles. This type of plasma can be found throughout both space and terrestrial environments. Wildfires, for example, generate dusty plasmas when charged particles of soot mixed with smoke. In this new study—published in the journal Proceedings of the National Academy of Sciences (PNAS)—a team of researchers describes how their trained ML model successfully provided the most detailed description of dusty plasma physics yet, creating precise predictions for non-reciprocal forces. 'Our AI method is not a black box: we understand how and why it works,' Justin Burton, a co-author of the study from Emory, said in a press statement. 'The framework it provides is also universal. It could potentially be applied to other many-body systems to open new routes to discovery.' Put simply, non-reciprocal forces (as their name suggests) occur when forces exerted between two particles in a plasma are not the same. The authors describe the phenomenon as two boats impacted by the wake of the other—relative position can impact the particles' attractive or repulsive forces. 'In a dusty plasma, we described how a leading particle attracts the trailing particle, but the trailing particle always repels the leading one,' Ilya Nemenman, another co-author of the study from Emory, said in a press statement. 'This phenomenon was expected by some but now we have a precise approximation for it which didn't exist previously.' The ML algorithm was also able to correct some theoretical misconceptions about dusty plasma. For example, scientists thought that the charge of the particle was proportional to its size, but the model confirms that while a larger particle does contain a larger charge, it isn't proportional, as it can also be influenced by density and temperature. They also found that the charge between particles isn't only influenced by the distance between two particles, but also by the particles' sizes. One the trickiest parts of this project, according to the authors, was designing the ML algorithm in the first place. Generally, AI acquires its abilities by being fed (or training on) datasets—give AI one million pictures of a monkey, and it'll get progressively better at identifying a monkey when it sees one. However, when it comes to discovering new physics, there isn't much training data to go on. So, the team had to create a structure that allowed it to work with the data it did have while still giving it latitude to explore unknown physics. 'I think of it like the Star Trek motto, to boldly go where no one has before,' Burton said. 'Used properly, AI can open doors to whole new realms to explore.' You Might Also Like The Do's and Don'ts of Using Painter's Tape The Best Portable BBQ Grills for Cooking Anywhere Can a Smart Watch Prolong Your Life? Solve the daily Crossword
Politico
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Kennedy to halt $500 million in vaccine projects
The planned cancellation of contracts includes work with Emory University and Tiba Biotech. Proposals from Pfizer, Sanofi Pasteur, CSL Seqirus, Gritstone and others will also be rejected, according to HHS. Rick Bright, who led HHS's Biomedical Advanced Research and Development Authority, or BARDA, from 2016 to 2020 — and criticized the Trump administration's early Covid response — slammed the decision, calling it a 'huge strategic misstep.' 'This decision signals a dangerous complacency,' Bright said in a text. 'Disinvesting from mRNA strips us of one of the fastest tools we have to contain the next pandemic, natural or deliberate. Pulling back from proven medical countermeasure platforms at a time of escalating global bio‑risks deeply compromises national security.' HHS said the cancellations impact 22 projects worth nearly $500 million — however, some contracts in their final stage will be 'allowed to run their course to preserve prior taxpayer investment.' The federal health department said it is instructing the Global Health Investment Corporation — which helps manage BARDA's technological investments — to cease mRNA-based equity investments. However, HHS said other mRNA technologies 'within the department are not impacted by this announcement.' HHS said future BARDA vaccine investments will focus on technologies such as whole-virus vaccines and other new immunization platforms.
